Pancreatic Ductal Adenocarcinoma (PDA) is a deadly disease with few effective treatment options. The PDA cancer cell is nurtured in a complex microenvironment comprised of multiple cell types admixed with matrix and signaling proteins. Like most complicated systems, it has been hard to accurately model the microenvironment in the lab. Our attempts to identify and therapeutically impact microenvironmental targets have and will continue to fail in the clinic without good models, so the need in this area is immediate and real. This innovative project goes far beyond insufficient human xenograft in nude mouse models to both understand and exploit innate dependencies that PDA cells have for cues from their microenvironment. We have invented flexible in vitro and in vivo systems to independently vary microenvironmental composition alongside the presence of drug and tumor cell genomic subtype in robust and dynamic preclinical models. These novel models are now poised to directly test the hypotheses that the microenvironment harbors discrete, unappreciated treatment targets in this difficult to treat disease, and that the transcriptional subtype of the cancer cell might independently impact how such treatments fare clinically. We plan to discover, prioritize and exploit crucial microenvironmental cofactors here i this 100% pancreatic cancer-relevant project through two specific aims focused on personalizing treatment of the PDA microenvironment by subtype. Specific Aim 1: To optimize treatment of the Quasi-Mesenchymal (QM-PDA) subtype by co-targeting the kinase MEK and extracellular interactions involved in resistance to inhibitors of MEK (MEKi). Aim 1.1: Describe the mechanism of Integrin V (ITGAV) dependence in the QM-PDA subtype by identifying the integrin subunit(s) involved, and defining the role(s) of TGF in the process. Aim 1.2: Validate the in vivo efficacy of MEKi combinations co-targeting either V Integrin or TGF receptors in a QM-PDA model. Specific Aim 2: To define and exploit pancreatic stellate cell (PSC)-derived factors that change drug response and/or affect metastatic behavior. Aim 2.1: Identify and inhibit novel PSC-generated signals that support growth and confer resistance to MEK inhibitors using Microenvironment Microarrays, to mimic the microenvironment in vitro. Aim 2.2: Genetically define PSC-derived factors affecting the metastatic process in vivo, by altering and co-transplanting activated, genetically modified PSCs in a syngeneic system.